A fundamental goal of automotive heating, ventilating, and air conditioning (HVAC) systems is to make vehicle occupants comfortable. In doing so, it is important to control such systems with fuel economy in mind.
In an attempt to measure and control the many variables that affect passenger comfort, modern automotive HVAC systems have many sensors and control actuators. A typical system might have a temperature sensor inside the cabin, one measuring ambient temperature outside and others measuring various temperatures of the system internal workings. The occupant may have some input to the system via a set point or other adjustment. Additional sensors measuring sun heating load, humidity, etc. might be available to the system. The set of actuators might include a variable speed blower, some means for varying air temperature, ducting and doors to control the direction of air flow and the ratio of fresh to recirculated air.
It falls to the controller to sort out the range of possible conditions, determine what is needed to economically achieve comfort, and coordinate the control of the set of actuators available. This multiple input, multiple output control problem may not fall into any convenient category of traditional control theory since fogging conditions may also be considered. The response of the system as well as the relationship between system variables and desired performance, fuel economy, is rarely linear. Also, it is important to note that despite all the actuators and variables available for control, there may exist conditions under which good fuel economy may not be achievable.
Due to practical considerations of size, energy consumption, cost and the wide conceivable range of conditions that automobiles are exposed to, the system plant may simply not be able to supply what is needed. All these considerations lead to a control problem that is far from what is usually encountered in traditional control theory.
In the face of these difficulties, most control system designs have used what is familiar--linear control--and supplemented it by patched-in specific responses to handle special circumstances where necessary. In other words, typical automobile automatic climate control systems use linear proportional control to maintain the interior environment. However, there are significant limitations of linear proportional control when viewed from the standpoint of fuel economy. For example, there are certain control situations in any HVAC system that are inherently nonlinear.
The linear approach has obvious limitations when dealing with nonlinear situations. All HVAC systems behave nonlinearly in various regions of their operation. The transfer of heat as a function of blower speed is nonlinear. The onset of any plant output limitation affects de:sired response in a nonlinear fashion. Factors affecting plant limitations may be tracked via additional sensors--for example, engine coolant temperature (ECT) correlates with heater core temperature--but again, the relationship is nonlinear. The usual approach to handling special nonlinear situations is to use logic-based modification of the usual linear strategy when these situations are detected. Thus, in cold weather, when ECT is below a certain threshold indicating that the heater core cannot warm the cabin, the blower would be shut off.
In addition to the current difficulties, new vehicle lines create additional problems that are not easy to overcome. The reduction in interior and under hood package space in current vehicle designs has caused the transfer function for discharge temperature to be even more nonlinear, especially when operating at the extremes of ambient temperature.